Shocker: Medical Research Frequently Bogus

Shocker: Medical Research Frequently Bogus

Wednesday, July 08, 2009 by: S. L. Baker, features writer.

(NaturalNews) If you read research in a scientific or medical journal, especially one that is peer-reviewed, you know it is presented as accurately as possible, right? Researcher Daniele Fanelli of the University of Edinburgh decided to study the scientists doing the studies to see if she could find the answer.

After conducting the first meta-analysis of surveys questioning scientists about their misbehavior behind the scenes -- notably, falsifying their research -- she came up with results that are nothing less than shocking. It turns out that researchers apparently alter or just plain make up data far more frequently than previously estimated. And the practice seems to be particularly high in medical and drug research.

Bogus science isn't new, of course. In recent years researcher Hwang Woo-Suk's stem-cell lines were shown to be fake and cancer researcher Jon Sudbo was outed for making up cancer trials. These and other examples have demonstrated that made-up research can be easy to publish, even in some of the top, prestigious journals.

The media and many in the scientific community have mostly explained these cases as rare instances of non-ethical researchers. However, Fanelli's study, just published in the journal PLoS ONE, suggests scientific misconduct and outright fraud might be relatively frequent.

Previous estimates on bogus research have been based on not-very-accurate indirect data such as counting official retractions of scientific papers or random audits that show data were incorrect. Other researchers have tried simply using surveys to ask scientists all over the world about fraudulent research practices. But because of many different methods and questions used in the surveys, those results have been labeled inconclusive.

To try and sort all this out, Fanelli conducted a meta-analysis to specifically focus on behaviors that actually distort scientific knowledge. She excluding data about plagiarism and other kinds of professional malpractice and concentrated on documenting the frequency of scientists who recalled having committed a particular fraudulent activity at least once, or who knew a fellow scientist who did.

The results from all the surveys showed that only about two percent of scientists admitted to either making up or altering data to improve the outcome of a study at least once. Because the surveys asked very sensitive questions, Fanelli pointed out that it likely that some respondents did not reply honestly, especially when asked about their own activities. So the two percent figure is probably a very conservative estimate.

A much larger number, around 34 percent, admitted to other questionable research practices that can totally skew the results of a study -- including "failing to present data that contradict one's own previous research" and "dropping observations or data points from analyses based on a gut feeling that they were inaccurate." What's more, 14 percent of the scientists said they knew someone who had fabricated, falsified or altered data, and the vast majority, around 72 percent, said they knew someone who had taken part in other questionable research practices.

In all the surveys examined by Fanelli's meta-analysis, misconduct was reported most frequently by drug and medical researchers. So what's the bottom line? Either scientists studying drugs or working on health issues are more open and honest than other researchers when they answer questions about bogus research, or frauds, trickery and bias are disturbingly more frequent in pharmacology and medicine. In a statement to the media, Fanelli concludes the last interpretation supports growing suspicions that industrial sponsorship, including the mega-bucks provided by Big Pharma, could be severely distorting scientific evidence to promote commercial treatments and drugs.

Reference:Fanelli D (2009), How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data. PLoS ONE 4(5): e5738. doi:10.1371/journal.pone.0005738

For more information:http://www.nature.com/news/specials...http://dx.plos.org/10.1371/journal....http://www.nytimes.com/2006/01/19/n...http://www.sjweh.fi/show_abstract.p...